Senior Machine Learning Operations Engineer
24 hours ago
At Unreal Gigs, we're pushing the boundaries of machine learning operations (MLOps) to drive innovation and transform industries. As a Senior ML Operations Engineer, you'll play a critical role in building and maintaining the infrastructure and processes that enable the deployment, monitoring, and management of machine learning models at scale.
Key Responsibilities:- Infrastructure Design: Design and implement scalable and reliable infrastructure for deploying and serving machine learning models, leveraging cloud platforms and containerization technologies.
- Model Deployment: Develop automated pipelines for deploying machine learning models into production environments, ensuring consistency, reliability, and reproducibility.
- Monitoring and Alerting: Implement monitoring and alerting systems to track model performance, data drift, and other metrics, enabling proactive detection and mitigation of issues.
- Model Versioning and Management: Establish version control and management processes for machine learning models, enabling easy tracking, rollback, and experimentation.
- Continuous Integration/Continuous Deployment (CI/CD): Implement CI/CD pipelines for automating model training, testing, and deployment, reducing time to market and improving agility.
- Scalability and Efficiency: Optimize the performance and scalability of machine learning infrastructure, leveraging techniques such as distributed computing, parallelization, and resource management.
- Security and Compliance: Ensure machine learning systems comply with security and privacy standards, implementing access controls, encryption, and other security measures as needed.
- Documentation and Best Practices: Document MLOps processes, best practices, and standards, providing guidance and training to data scientists and engineers.
- Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and DevOps teams, to streamline the machine learning lifecycle and drive continuous improvement.
- Research and Innovation: Stay informed about the latest advancements in MLOps tools and technologies, exploring innovative approaches and techniques to enhance machine learning operations.
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
- 5+ years of experience in software engineering, DevOps, or related roles, with a focus on building and maintaining infrastructure for machine learning operations.
- Strong understanding of machine learning concepts and techniques, with experience working with data science teams and machine learning models.
- Proficiency in programming languages such as Python, Java, or Scala, and experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with containerization technologies such as Docker and orchestration tools such as Kubernetes.
- Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or MLflow.
- Experience with CI/CD pipelines, version control systems, and automation tools such as Jenkins, GitLab, or CircleCI.
- Strong problem-solving skills and analytical thinking, with the ability to troubleshoot complex issues and optimize system performance.
- Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
- Competitive salary: The industry standard salary for Senior ML Operations Engineers typically ranges from $170,000 to $250,000 per year, depending on experience and qualifications.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous vacation and paid time off.
- Professional development opportunities, including access to training programs, conferences, and workshops.
- State-of-the-art technology environment with access to cutting-edge tools and resources.
- Vibrant and inclusive company culture with opportunities for growth and advancement.
- Exciting projects with real-world impact at the forefront of MLOps innovation.
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